Identifying the number of unreported cases in SIR epidemic models

A Ducrot; P Magal; T Nguyen; G F Webb

doi:10.1093/imammb/dqz013

Identifying the number of unreported cases in SIR epidemic models

Math Med Biol. 2020 May 29;37(2):243-261. doi: 10.1093/imammb/dqz013.

Authors

A Ducrot¹, P Magal², T Nguyen², G F Webb³

Affiliations

¹ Normandie University, UNIHAVRE, LMAH, FR-CNRS-3335, ISCN, Le Havre, France.
² University of Bordeaux, CNRS, Bordeaux INP, IMB, UMR, Talence, France.
³ Mathematics Department, Vanderbilt University, Nashville, TN, USA.

PMID: 31271207
DOI: 10.1093/imammb/dqz013

Abstract

An SIR epidemic model is analysed with respect to the identification of its parameters and initial values, based upon reported case data from public health sources. The objective of the analysis is to understand the relationship of unreported cases to reported cases. In many epidemic diseases the reported cases are a small fraction of the unreported cases. This fraction can be estimated by the identification of parameters for the model from reported case data. The analysis is applied to the Hong Kong seasonal influenza epidemic in New York City in 1968-1969.

Keywords: epidemic model; reported cases; transmission rate; turning point; unreported cases.

Publication types

Historical Article

MeSH terms

Basic Reproduction Number / statistics & numerical data
Computational Biology
Disease Susceptibility
Epidemics / history
Epidemics / statistics & numerical data*
History, 20th Century
Humans
Influenza, Human / epidemiology
Influenza, Human / history
Influenza, Human / transmission
Mathematical Concepts
Models, Biological*
New York City / epidemiology